One of the types of objects in Praat. A DataModeler tries to fit N data points (x_i, y_i) as lying on a particular kind of model function f(x; p) that depends on M parameters p. The parameters p are determined by minimizing the chi squared function χ²(p)=Σ ((y_i - f(x_i, p))/σ_i)², where the sum is over all N data points.

If the individual uncertainties σ_iof the data are not known before hand, the model parameter are determined by assuming that all uncertainties σ_i are equal. However an independent assessment of the goodness-of-fit cannot be determined in this case. A good guess for σ² for this case could be σ²=Σ (y_i - f(x_i, p))².

Drawing